I do see what you’re saying. You can account for all of these factors and it still turns out that, largely, individual LLM use just doesn’t use that much power compared to most things people do day to day. Inference is so cheap that even dozens of requests don’t amount to much. I could look up and give you a bunch of numbers, but I don’t think that’s likely to convince anyone who doesn’t do the research themselves. It’s so easy to come up with sources that say what you want. I’d encourage you to actually look into this yourself.

Training costs are higher, but you train once and use repeatedly. Right now, total training costs are stupidly high, but that’s because we’ve got an arms race between the frontier labs to spend as much money and compute as they can for truly marginal gains in quality. The solution to that problem isn’t for individuals to stop using AI, it’s to stop those assholes from wasting so much power.

Individual LLM use is so cheap, that it really isn’t worth wasting people’s energies thinking about limiting that. Instead of being distracted by attempts to make this an issue of personal responsibility, we should be focusing on what will actually make a difference. We should be focused on supporting policies that lead to systemic change. A carbon tax would change corporate behavior right quick, and not just for AI companies.

I’m going to simplify a little here, so don’t take this completely at face value.

Models are, quite literally, long series of numbers (called weights). A model might store the weights in 16 bit numbers (that is, 16 binary digits). The size of the model (and how much memory it needs) is determined by how many weights there are, and how many bits each weight takes. You can take a 16 bit model and rework it to use 8 bit, or even 4 bit numbers. The result intuitively behaves a lot like the same model, but with less precision to the weights. That makes the model take way less space in ram, but also makes it more likely for concepts (encoded in the weights) to overlap, which impacts model quality. Often the effect is that fine distinctions get lost.

In recent years, I’ve started feeling comfortable recommending it over Windows.

Sure, I’ll still tell friends and family to just get a Mac. But if you’re not going to do that, Windows is just a worse experience in most the important ways at this point, even for a non-techie user.

It is absolutely possible to run 100% locally, but in practice, at the high end, only quantized models. The full size top end models require hundreds of GB of video ram, and while you can buy that, it’s stupidly expensive. Quantized models can often perform nearly as well with a small fraction of the ram, but they do sacrifice a little in precision.

These models (well the good ones) ultimately all trace their origins to what you’d likely consider “stolen” data. Whether that’s ethical is debatable. If you’re in the “information should be free” camp, there may not be an issue here.

As for the power/environmental impact, for what they do LLMs are actually very low impact per-request. If you’re concerned about your personal AI power use, then I hope you never fly in an airplane, and minimize your driving because those are much bigger issues.

It’s the scale of use that makes AI an environmental problem, and that’s a question about corporate use of AI, not personal use of AI.

Honestly, this is nothing new.

Listening to ChatGPT is a solid improvement over listening to Tucker Carlson.

Don’t get me wrong, it’s not good! I don’t exactly trust the Sam Altmans of the world. But this is the same circus, different clowns.

Right?

The information is out there if you know how to sift through the nonsense.

Though trying to do this with nutrition really is hard mode. I don’t know of another topic that’s quite as flooded with nonsense.

I’d add that traditional search can’t reasonably hope to compete with AI in this environment. If you’re running a traditional search engine right now, there’s a real argument that the best business decision is to accelerate the enshitification to capture as much value as you can from your remaining audience while you still have it.

This is the usual cycle with these sorts of technologies - once a replacement arrives, the natural choice is to shift from growth to exploitation.

This is going to get worse before it gets better.

this is all done with custom models by individuals.

This is really important for people to understand.

Powerful open weight models are already out there. Anyone can download them and run them. There is no possibility for government control of AI content without North Korean style internet controls.

Politicians and corporations will absolutely start trying to push for more controls. They will tell you to “think of the children” and they will use this to take power for themselves, knowing full-well that they can’t actually meaningfully prevent this from happening. We need people to understand that the push for control here has nothing to do with morality or protecting anyone.

The government doesn’t get to decide you’re guilty

I want to call out how important this is. This is one of the strongest checks against corruption in the countries that have it.

As a concrete example, if we didn’t have this in the US, I’m not sure there would be much to stop Trump’s justice department from bringing cases against Trump’s enemies in front of Trump appointed judges, and sending them to jail. Jack Smith and James Comey would likely be in jail right now if we didn’t have jury trials.

Curry is a global cuisine.

It may originate in India, but it has been incorporated into local cuisines all over the world. Most countries in Asia have their own versions of curry at this point. I’d argue that the UK does too, even if they call it “Indian”. Even the concept of curry as a category of food is largely a British invention, and many of the things we’ve been calling curry for more than a hundred years have little relation to Indian food.

Also, India is a large and diverse country. Many Indians don’t eat beef, but there are absolutely whole populations of Indians who eat beef curry regularly.